PBPK and Population Modeling Seamlessly Linked to Clinical Trial Simulation in an Open-Source Software Platform

该项目的目标是开发一个全面的、开源的生物等效性软件平台 研究设计.该平台的组成部分将实施一个基于生理学的人口建模框架， 与试验模拟器集成的基于LY的药代动力学（PBPK）模型。该框架将包括：1）模型 适用于各种化合物和给药途径的结构; 2）多样化和稳健的参数 和用于群体建模的非参数方法，以更新先前的PBPK模型参数值分布， 个体数据; 3）采用标准和新型最佳抽样策略模拟各种BE试验设计; 4） 集成工作流程的软件实现。为了建立框架，项目将侧重于以下方面 目标与工作流程一致。目的1：在现有的静脉注射和皮下注射途径中增加吸入和皮肤渗透途径， 开放系统药理学（OSP）套件中的口服途径和体外-体内制剂/溶出度相关性 module.目的2：整合各种参数和非参数人口算法的基础上部分的Pmet- rics软件包，用于在获得个体数据时更新PBPK模型。目标3：通过重新开发BE试验模拟器， 利用OSP和Pmetrics中的现有功能来模拟各种BE试验设计的输出， 评级标准和新的最佳抽样算法以及用于样本量计算和分析的现有R模块 预测的试验结果。目标4：实现一个无缝集成的软件工作流程， 和模拟，托管在OSP平台上，并使用最先进的工程技术来创建一个免费可用的，开放的， 源产品。

The goal of this project is to develop a comprehensive, open-source software platform for bioequivalence (BE) study design. Components of the platform will implement a framework for population modeling based on physiological- ly-based pharmacokinetic (PBPK) models integrated with a trial simulator. The framework will consist of: 1) Model structures appropriate for a wide range of compounds and routes of administration; 2) Diverse and robust parametric and nonparametric methods for population modeling to update prior PBPK model parameter value distributions with individual data; 3) Simulation of a variety of BE trial designs with standard and novel optimal sampling strategies; 4) Software implementation of an integrated workflow. To build the framework, the project will focus on the following aims that align with the workflow. Aim 1: Add inhalational and dermal penetration routes to existing intravenous and oral routes in the Open Systems Pharmacology (OSP) Suite and an in vitro-in vivo formulation/dissolution correlation module. Aim 2: Integrate a variety of parametric and nonparametric population algorithms based in part upon the Pmet- rics package for R to update PBPK models when individual data are available. Aim 3: Develop a BE trial simulator by re- purposing existing capabilities within OSP and Pmetrics to simulate output for a wide range of BE trial designs, incorpo- rating standard and novel optimal sampling algorithms and existing R modules for sample size calculations and analysis of predicted trial outcomes. Aim 4: Implement a seamlessly integrated software workflow of model building, updating and simulating, hosted on the OSP platform, and using state of the art engineering to create a freely available, open- source product.